Entrepreneurial Operations | 2018-19

This Course shows a new entrepreneur the inside workings of a business process, viewed with precision. Professor Rajaram begins with a scientific understanding of operations management, demonstrating the steps in process analysis, and then discusses variability and its impact on a process, using Little’s Law to illustrate the assessment, and shows how and when to use work-in-progress buffers. He completes the course by addressing various ways to reduce process variability and its effect on lead times.

Faculty

Professor Kumar Rajaram

Professor Kumar Rajaram

Professor

Kumar Rajaram is a Professor of Operations and Technology Management at the UCLA Anderson School of Management. Professor Rajaram’s current research interests include improving operations in the health care industry, non-profit sector and in the process manufacturing sectors including food processing, pharmaceuticals and the petrochemical industry. He has focused on developing analytical models of complicated systems with a strong emphasis on practical implementation. His work has been published in leading research journals such as Operations Research, Management Science, Manufacturing and Service Operations Management, Marketing Science and the European Journal of Operational Research. He has been awarded the Eric and ‘E’ Juline Faculty Excellence in Research Award at the UCLA Anderson School.

Professor Rajaram has developed a new control paradigm called “Robust Process Control” to increase the productivity of large-scale industrial processes. By focusing on the design and control of these processes in operational environments, this technique has resulted in four-fold increases in productivity in several types of industrial processes. These methods have been implemented at several process companies worldwide. This work was awarded the prestigious Franz Edelman finalist award for outstanding applications of operations research and management science techniques to practice by the Institute for Operations Research and the Management Sciences (INFORMS). He has also developed techniques to better balance supply with demand for products with short life cycles and highly unpredictable demand. This work has been applied at several large fashion retailers in Europe and North America and has resulted in substantial improvements to profitability at these sites.

At the UCLA Anderson School, Professor Rajaram teaches the MBA core course on operations and technology management, various Executive Education courses and doctoral level courses on operations management and models for operations design, planning and control. He has been awarded the George Robbins Award, the Citibank Award and the Neidorf “Decade” Award for excellence in teaching at the UCLA Anderson School.

Education
Ph.D. Operations Management, 1998, The Wharton School, University of Pennsylvania
M.A. Managerial Science and Applied Economics, 1997, The Wharton School, University of Pennsylvania
M.S. Industrial Engineering and Operations Research, 1993, University of Massachusetts at Amherst
M.Sc. Mathematics, with Honors 1991, Birla Institute of Technology and Science, Pilani, India
B.E. Electrical and Electronics Engineering, with Honors 1991, Birla Institute of Technology and Science, Pilani, India

Course Learning Objectives:

By the end of this course, you will be able to:

  • Analyze a process scientifically to find its bottleneck/s and evaluate options for improving and balancing the process.
  • Integrate buffers appropriately into your work processes to maximize smooth production output.
  • Use Little’s Law to investigate the impact of variability and cycle times on lead times and bottlenecks, then systematically reduce those impacts.

Syllabus

Introduction to Operations Management

Module Learning Objectives:

  • Module Learning Objectives:As a result of participating in this module, you will be able to:
    • Explain basic process analysis terms to a novice in operations management.
    • Create a logical operational process in its correct order, labeling each step as input, tasks, flow, storage, and output.
    • Using a logical process, correctly calculate/determine its bottleneck, idle time, direct labor content, direct labor utilization, and whether the process is “in balance.”

Module Components:

  • Video Lecture 1: Introduction to Operations Management
  • Video Lecture 2: What Is a Process and Why Study Process Analysis?
  • Video Lecture 3: Basic Definitions and an Illustrative Example
  • Reading 1: Introduction to Business Process Improvement
  • Reading 2: Unblocking Bottlenecks: Fixing Unbalanced Processes
  • Reading 3: How to Manage Bottlenecks in Operations Management
  • Assignment: Case Study on Ultimate Teeth
  • Check for Understanding Assessment

Illustrative Analysis

Module Learning Objectives:

As a result of participating in this module, you will be able to:

  • Use data to describe a current process in terms of its efficiency and its economic measures.
  • Analyze an existing process to find options for improving its efficiency and related economic measures.
  • For one change option, analyze the data to determine if it would or would not be an improvement to the existing process and make a recommendation.

Module Components:

  • Video Lecture 1: Illustrative Example: Analysis
  • Video Lecture 2: Illustrative Example: Improvement
  • Video Lecture 3: A Framework for Process Analysis
  • Reading 1: Improving Business Processes: Streamlining Tasks to Improve Efficiency
  • Reading 2: Handbook for Basic Process Improvement
  • Reading 3: Business Process Management: A Comprehensive Survey
  • Assignment: Case Study on Ultimate Teeth, continued

Operations Management: Modeling, Analyzing & Optimizing Processes, Part I

Module Learning Objectives:

As a result of participating in this module, you will be able to:

  • Calculate the range and the standard deviation of the variability in an existing process.
  • Evaluate the value of incorporating a work-in-progress buffer into an existing process and recommend for/against it.
  • Evaluate each of the managerial levers that can reduce variability to determine its suitability for addressing a problem with variability in a process.

Module Components:

  • Video Lecture 1: Fundamentals of Managing the Impact  of Variability
  • Video Lecture 2: How Variability Affects the Process
  • Video Lecture 3: How Variability Affects Operations’ Performance and How to Reduce Variability
  • Reading 1: Variability, Throughput, and Cycle Time in Manufacturing and Product Development
  • Reading 2: Secrets to Variability Reduction
  • Reading 3: Analysis and Control of Variation: Using Process Control to Reduce Variability: Comparison of Engineering Process Control with Statistical Process Control
  • Assignment: Case Study on Ultimate Teeth, continued
  • Check for Understanding Assessment

Operations Management: Modeling, Analyzing & Optimizing Processes, Part II

Module Learning Objectives:

As a result of participating in this module, you will be able to:

  • Calculate the lead time for a process, using Little’s Law and provided data.
  • Follow the directives of the P-K Formula to focus on reducing variability to remove some of the randomness of the arrival of orders, thus reducing lead time; consider each of the three main types of managerial levers: external policies, internal polices, and technology.

Module Components:

  • Video Lecture 1: Business Operations: Managing the Impact of Variability on Lead Times
  • Video Lecture 2: Lead Times in Processes
  • Video Lecture 3: Action Plan
  • Reading 1: Manufacturing Lead Time – What is it?
  • Reading 2: Manufacturing Critical-path Time: A Measure of True Lead-Time
  • Reading 3: Lead Time Reduction
  • Assignments: Case Study on Ultimate Teeth, continued

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